Paper Citation Record · LEDGER

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting

As of 13 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2506.05009.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.05009 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:33:52.166232Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

verified exact0
verified fuzzy31
unresolved7
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f9cf4c18-8728-4941-86d7-6a3914b37395 · outbound

This paper cites Mip-nerf 360: Unbounded anti-aliased neural radiance fields.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Mip-nerf 360: Unbounded anti-aliased neural radiance fields

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T10:33:46.886435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38526310-17d7-4e18-b94f-ff857a675c75 · outbound

This paper cites Barron, Ben Mildenhall, Dor Verbin, Pratul P.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Barron, Ben Mildenhall, Dor Verbin, Pratul P

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:34:02.215533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1d7d3612-db18-4093-9d1e-dc1e80c3ff55 · outbound

This paper cites Se- mantickitti: A dataset for semantic scene understanding of lidar sequences, 2019.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Se- mantickitti: A dataset for semantic scene understanding of lidar sequences, 2019

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:34:01.832005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 901949b3-1eb2-47f1-863c-c86cb63ab0ec · outbound

This paper cites Pointmixup: Augmentation for point clouds.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Pointmixup: Augmentation for point clouds

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:34:01.537428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 27c1fb9a-c355-4138-8005-a91637d9d056 · outbound

This paper cites Chang, Manolis Savva, Maciej Hal- ber, Thomas Funkhouser, and Matthias Nießner.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Chang, Manolis Savva, Maciej Hal- ber, Thomas Funkhouser, and Matthias Nießner

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:34:01.244356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 445e8533-06e5-4d42-80e1-78debeea04dd · outbound

This paper cites Carla: An open urban driv- ing simulator.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Carla: An open urban driv- ing simulator

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:34:00.922097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2b9fa2f9-5d95-4c0d-a233-4e6654e0670e · outbound

This paper cites Moeslund.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Moeslund

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:34:00.648347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 72ade8c6-032b-46d5-b42e-a68619bf7a61 · outbound

This paper cites Sugar: Surface- aligned gaussian splatting for efficient 3d mesh reconstruc- tion and high-quality mesh rendering.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Sugar: Surface- aligned gaussian splatting for efficient 3d mesh reconstruc- tion and high-quality mesh rendering

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:34:00.363258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a05b6220-53a1-48e9-90bb-6c094024a7ed · outbound

This paper cites Baking neural ra- diance fields for real-time view synthesis.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Baking neural ra- diance fields for real-time view synthesis

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:34:00.082557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6cf0c143-3c65-487a-ac35-f41c16411ca4 · outbound

This paper cites 2d gaussian splatting for geometrically ac- curate radiance fields.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting 2d gaussian splatting for geometrically ac- curate radiance fields

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:59.801320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0c3e5e4e-d85b-4472-bb56-aca85138b9cd · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering, 2023.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting 3d gaussian splatting for real-time radiance field rendering, 2023

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:59.555747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0eb8cb02-02a0-44af-8840-4b5d34c07ec5 · outbound

This paper cites Design and use paradigms for gazebo, an open-source multi-robot simula- tor.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Design and use paradigms for gazebo, an open-source multi-robot simula- tor

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:59.198398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0df1b9bb-f0fd-48ae-a797-259712d0ff8a · outbound

This paper cites Pointaugment: an auto-augmentation framework for point cloud classification.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Pointaugment: an auto-augmentation framework for point cloud classification

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:58.863635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3a5896f4-e4b4-4596-89fe-d2abd069519a · outbound

This paper cites Pointcnn: Convolution on x-transformed points.Advances in neural information processing systems, 31, 2018.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Pointcnn: Convolution on x-transformed points.Advances in neural information processing systems, 31, 2018

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:58.580417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 68f2085f-04f1-4c3e-8503-f7d9335682c6 · outbound

This paper cites Adfactory: An effective framework for gen- eralizing optical flow with nerf.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Adfactory: An effective framework for gen- eralizing optical flow with nerf

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:58.212615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 09821c71-5af5-4b7b-a38a-ab74b61e0939 · outbound

This paper cites an unresolved cited work.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:33:57.963914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4223f0e6-2953-4f2e-8ac6-715e139fed8a · outbound

This paper cites NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T10:33:49.050729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0f9626e-28fd-42a3-b3a4-49cf8895c4c8 · outbound

This paper cites Ouster os0: High-precision ultra wide, 2024.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Ouster os0: High-precision ultra wide, 2024

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:57.632378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 32c4eaa2-5198-4808-8cbb-252ec293d4c7 · outbound

This paper cites Oa-cnns: Omni- adaptive sparse cnns for 3d semantic segmentation, 2024.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Oa-cnns: Omni- adaptive sparse cnns for 3d semantic segmentation, 2024

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:57.339925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 09a5c7e3-433a-4442-ab4a-0774e09ca6d5 · outbound

This paper cites Qi, Hao Su, Kaichun Mo, and Leonidas J.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Qi, Hao Su, Kaichun Mo, and Leonidas J

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:57.008955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8ce47397-d968-44a4-a332-9220e03dc492 · outbound

This paper cites Qi, Li Yi, Hao Su, and Leonidas J.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Qi, Li Yi, Hao Su, and Leonidas J

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:56.727297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ba6feca9-a424-47d0-b837-a65294630b79 · outbound

This paper cites Merf: Memory-efficient radiance fields for real- time view synthesis in unbounded scenes.ACM Transactions on Graphics (TOG), 42(4):1–12, 2023.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Merf: Memory-efficient radiance fields for real- time view synthesis in unbounded scenes.ACM Transactions on Graphics (TOG), 42(4):1–12, 2023

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:56.436257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 80cee2f6-b32a-49c2-82b9-61f9c7c1c07b · outbound

This paper cites Self-evolving depth-supervised 3d gaussian splatting from rendered stereo pairs.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Self-evolving depth-supervised 3d gaussian splatting from rendered stereo pairs

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:56.140838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b97f454c-2224-473a-b392-f9c84147aeb1 · outbound

This paper cites Structure-from-motion revisited.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Structure-from-motion revisited

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:55.846271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation df668533-bbd7-44eb-9219-049c597f320a · outbound

This paper cites Scalability in perception for autonomous driving: Waymo open dataset.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Scalability in perception for autonomous driving: Waymo open dataset

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T10:33:50.161066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45cc5ef6-4d9b-46da-ad57-bd6596f954f5 · outbound

This paper cites 3d segmentation of humans in point clouds with syn- thetic data.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting 3d segmentation of humans in point clouds with syn- thetic data

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:55.459445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e02c62d5-2b09-42ad-a9bb-fc14cc3fcdde · outbound

This paper cites Nerf-supervised deep stereo.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Nerf-supervised deep stereo

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:55.106507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e8b0b9b7-a58e-47bb-b465-51e6ba143b65 · outbound

This paper cites Attention is all you need.Advances in Neural Information Processing Systems, 2017.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Attention is all you need.Advances in Neural Information Processing Systems, 2017

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T10:33:50.596867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 860eb5a7-87c4-46a8-93e4-9d53acfba375 · outbound

This paper cites KISS-ICP: In Defense of Point-to-Point ICP – Simple, Accurate, and Robust Registration If Done the Right Way.IEEE Robotics and Automation Letters (RA-L), 8(2):1029–1036, 2023.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting KISS-ICP: In Defense of Point-to-Point ICP – Simple, Accurate, and Robust Registration If Done the Right Way.IEEE Robotics and Automation Letters (RA-L), 8(2):1029–1036, 2023

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:54.786730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3156034d-2ebb-4c7d-a534-86ed60cf4c46 · outbound

This paper cites Auto- matic generation of synthetic lidar point clouds for 3-d data analysis.IEEE Transactions on Instrumentation and Mea- surement, 68(7):2671–2673, 2019.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Auto- matic generation of synthetic lidar point clouds for 3-d data analysis.IEEE Transactions on Instrumentation and Mea- surement, 68(7):2671–2673, 2019

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:54.530315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0b30052b-581b-481a-a73a-4342aa84ada1 · outbound

This paper cites Dynamic graph cnn for learning on point clouds.ACM Transactions on Graphics (tog), 38(5):1–12, 2019.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Dynamic graph cnn for learning on point clouds.ACM Transactions on Graphics (tog), 38(5):1–12, 2019

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:54.212221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3654db27-890f-48fc-92e6-81e2ce1e17f9 · outbound

This paper cites Point transformer v2: Grouped vector atten- tion and partition-based pooling.Advances in Neural Infor- mation Processing Systems, 35:33330–33342, 2022.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Point transformer v2: Grouped vector atten- tion and partition-based pooling.Advances in Neural Infor- mation Processing Systems, 35:33330–33342, 2022

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:53.839804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8c325adf-9505-49e0-b7aa-4e50cf014516 · outbound

This paper cites Point transformer v3: Simpler, faster, stronger, 2024.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Point transformer v3: Simpler, faster, stronger, 2024

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:53.569386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5fa2a170-054c-48aa-b31c-336e628e2422 · outbound

This paper cites Transfer Learning from Synthetic to Real LiDAR Point Cloud for Semantic Segmentation.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Transfer Learning from Synthetic to Real LiDAR Point Cloud for Semantic Segmentation

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T10:33:51.413379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66312b6d-5ca0-4e94-a2c2-eab54797e859 · outbound

This paper cites Bakedsdf: Meshing neural sdfs for real- time view synthesis.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Bakedsdf: Meshing neural sdfs for real- time view synthesis

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:53.326963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 320c1327-a8cd-4a26-b757-b26c134811be · outbound

This paper cites Gaussian Opacity Fields: Efficient Adaptive Surface Reconstruction in Unbounded Scenes.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Gaussian Opacity Fields: Efficient Adaptive Surface Reconstruction in Unbounded Scenes

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T10:33:51.744346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a427c2f-bd9f-4750-b543-318d033c69c0 · outbound

This paper cites A lidar point cloud generator: from a virtual world to autonomous driving.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting A lidar point cloud generator: from a virtual world to autonomous driving

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:53.085100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 26a78fc2-cb52-4df5-9e37-a38f6c631d0b · outbound

This paper cites Place: Proximity learning of articulation and con- tact in 3d environments.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Place: Proximity learning of articulation and con- tact in 3d environments

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:33:52.803108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a93f0aa1-8681-4354-a956-337912fcd2f3 · outbound

This paper cites Point transformer.

Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting Point transformer

Reference 39

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T10:33:52.524366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.